Meprop [1]} has only experiments on MLP. [2]} supplements the CNN evaluation on the basis of Meprop [1]}. However, their chosen networks are unrepresentative because they are too naive to be adopted in practical applications. Based on [2]}, MSBP [5]} makes further improvements, which is comparing with our method as illustrated in Table. REF . Our proposed algorithm can achieve higher sparsity than MSBP while keeping a better accuracy than baseline and MSBP on CIFAR-10.
More importantly, the experiment result also shows that our work is also well performed on ImageNet which is more challenging but has not been evaluated in existing works.
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